
Since the start of the COVID-19 health crisis, gross domestic product (GDP) has continued to fall in the U.S. In fact, the GDP collapsed at a 32.9% annualized rate last quarter, which is the deepest decline since 1947. But as some states throughout the U.S. begin to relax their stay-at-home orders and start to reopen businesses, economists are taking note of how this will affect the nation’s recovery as a whole. When it comes to tracking the nation’s economic recovery, economists and policymakers need to account for all of the factors that will influence the outcome. This includes tracking the performance of individual states and understanding each state’s trajectory and recovery prospects. There are many factors that will impact each state’s trajectory for recovery. One example, in particular, can be seen in a state’s preparedness level and rainy day fund that’s set aside for emergencies. At the onset of the pandemic, many states were unprepared for the financial crisis. The Government Finance Officers Association recommends that states set aside at least two months of operating expenses in their rainy day funds – or roughly 16% of their general fund. However, although some states had set aside some budget to prepare for a recession, it was simply not enough. Only a few states were able to fulfill this requirement. Other factors that will impact each state’s recovery include: the efficiency of its unemployment program, state lockdown measures, and the concentration of jobs in vulnerable industries. Our new white paper, featuring key insights from Joseph Mayans, Principal Economist with Advantage Economics, provides a deep dive on: The economic landscape at the onset of the pandemic Statewide discrepancies for unemployment programs, lockdown measures, and labor markets Underlying factors that determine a state’s recovery prospects Why tracking state-level economies is critical for national recovery Listen in as he describes the importance of having a different perspective when tracking the national economy and download the white paper for greater insights. Download White Paper Now

In 2015, U.S. card issuers raced to start issuing EMV (Europay, Mastercard, and Visa) payment cards to take advantage of the new fraud prevention technology. Counterfeit credit card fraud rose by nearly 40% from 2014 to 2016, (Aite Group, 2017) fueled by bad actors trying to maximize their return on compromised payment card data. Today, we anticipate a similar tsunami of fraud ahead of the Social Security Administration (SSA) rollout of electronic Consent Based Social Security Number Verification (eCBSV). Synthetic identities, defined as fictitious identities existing only on paper, have been a continual challenge for financial institutions. These identities slip past traditional account opening identity checks and can sit silently in portfolios performing exceptionally well, maximizing credit exposure over time. As synthetic identities mature, they may be used to farm new synthetics through authorized user additions, increasing the overall exposure and potential for financial gain. This cycle continues until the bad actor decides to cash out, often aggressively using entire credit lines and overdrawing deposit accounts, before disappearing without a trace. The ongoing challenges faced by financial institutions have been recognized and the SSA has created an electronic Consent Based Social Security Number Verification process to protect vulnerable populations. This process allows financial institutions to verify that the Social Security number (SSN) being used by an applicant or customer matches the name. This emerging capability to verify SSN issuance will drastically improve the ability to detect synthetic identities. In response, it is expected that bad actors who have spent months, if not years, creating and maturing synthetic identities will look to monetize these efforts in the upcoming months, before eCBSV is more widely adopted. Compounding the anticipated synthetic identity fraud spike resulting from eCBSV, financial institutions’ consumer-friendly responses to COVID-19 may prove to be a lucrative incentive for bad actors to cash out on their existing synthetic identities. A combination of expanded allowances for exceeding credit limits, more generous overdraft policies, loosened payment strategies, and relaxed collection efforts provide the opportunity for more financial gain. Deteriorating performance may be disguised by the anticipation of increased credit risk, allowing these accounts to remain undetected on their path to bust out. While responding to consumers’ requests for assistance and implementing new, consumer-friendly policies and practices to aid in impacts from COVID-19, financial institutions should not overlook opportunities to layer in fraud risk detection and mitigation efforts. Practicing synthetic identity detection and risk mitigation begins in account opening. But it doesn’t stop there. A strong synthetic identity protection plan continues throughout the account life cycle. Portfolio management efforts that include synthetic identity risk evaluation at key control points are critical for detecting accounts that are on the verge of going bad. Financial institutions can protect themselves by incorporating a balance of detection efforts with appropriate risk actions and authentication measures. Understanding their portfolio is a critical first step, allowing them to find patterns of identity evolution, usage, and connections to other consumers that can indicate potential risk of fraud. Once risk tiers are established within the portfolio, existing controls can help catch bad accounts and minimize the resulting losses. For example, including scores designed to determine the risk of synthetic identity, and bust out scores, can identify seemingly good customers who are beginning to display risky tendencies or attempting to farm new synthetic identities. While we continue to see financial institutions focus on customer experience, especially in times of uncertainty, it is paramount that these efforts are not undermined by bad actors looking to exploit assistance programs. Layering in contextual risk assessments throughout the lifecycle of financial accounts will allow organizations to continue to provide excellent service to good customers while reducing the increasing risk of synthetic identity fraud loss. Prevent SID

The early assessment for the automotive industry is that despite significant challenges at the onset of the pandemic, the industry continues to rebound.

The COVID-19 pandemic created a global shift in the volume of online activity and experiences over the past several months. Not only are consumers increasing their usage of mobile and digital channels to bank, shop, work and socialize — and anticipating more of the same in the coming months — they’re closely watching how businesses respond to their needs. Between late June and early July of this year, Experian surveyed 3,000 consumers and 900 businesses to explore the shifts in consumer behavior and business strategy pre- and post-COVID-19. More than half of businesses surveyed believe their operational processes have mostly or completely recovered since COVID-19 began. However, many consumers fear that a second wave of COVID-19 will further deplete their already strained finances. They are looking to businesses for reassurance as they shift their behaviors by: Reducing discretionary spending Building up emergency savings Tapping into financial reserves Increasing online spending Moving forward, businesses are focusing on short-term investments in security, managing credit risk with artificial intelligence, and increasing online customer engagement. Download the full report to get all of the insights into global business and consumer needs and priorities and keep visiting the Insights blog in the coming weeks for a deeper dive into US-specific findings. Download the report

In today’s uncertain economic environment, the question of how to reduce portfolio volatility while still meeting consumers’ needs is on every lender’s mind. With more than 100 million consumers already restricted by traditional scoring methods used today, lenders need to look beyond traditional credit information to make more informed decisions. By leveraging alternative credit data, you can continue to support your borrowers and expand your lending universe. In our most recent podcast, Experian’s Shawn Rife, Director of Risk Scoring and Alpa Lally, Vice President of Data Business, discuss how to enhance your portfolio analysis after an economic downturn, respond to the changing lending marketplace and drive greater access to credit for financially distressed consumers. Topics discussed, include: Making strategic, data-driven decisions across the credit lifecycle Better managing and responding to portfolio risk Predicting consumer behavior in times of extreme uncertainty Listen in on the discussion to learn more. Experian · Effective Lending in the Age of COVID-19

As the COVID-19 pandemic continues to create uncertainty for the U.S. economy, different states and industries have seen many changes with each passing month. In our July edition of the State of the Economy report, written by Principal Economist Joseph Mayans, we’ll be breaking down the data that financial institutions can use to navigate a recovery. Labor markets and state-level employment impact Prior to the pandemic, unemployment in the U.S. was at a 50-year low, at an astonishing rate of 3.5%. Following the start of the pandemic, research shows that unemployment rose from 6.2 million in February to 20.5 million in May 2020, and sent the unemployment rate soaring to 14.7%. However, the data from last month’s State of the Economy Report revealed that the unemployment rate began to decline, with 46 states seeing rises in new job opportunities. Although unemployment started to increase, many states (like Nevada) saw a 25.3% unemployment rate statewide. The numbers for June are much more promising, and reveal a continuous uptick in the number of jobs added. The unemployment rate in the U.S. also fell from 13.3% to 11.1%. The impact to industries COVID-19 had major impacts on every industry in the U.S., with the leisure and hospitality industry being the hardest-hit at 7.7 millions job lost. According to CNBC, “The large number of layoffs in this industry led the U.S. economy to its worst month of job losses in modern history.” However, job growth for the leisure and hospitality industry began to gain momentum in May, with 1.2 million jobs added. This can be attributed to a slow and gradual rollback of stay-at-home orders nationwide. As of June 2020, 4.8 million jobs have been added to this industry. The trade, transportation, and utilities, as well as education and health services, manufacturing, and business services industries also saw improvements in employment. The impact to retail sales Clothing stores, furniture, and sporting goods stores were only a few of the many retailers that saw heavy declines following lockdown orders. After two consecutive months of decline, retail sales finally rebounded by 17.7% in May, with the largest gains occurring in clothing stores (+188%). In June, retail sales continued to rise substantially, resulting in saw a v-shaped bounce. However, with unemployment benefits nearing the expiration date and the number of pandemic cases continuing to increase, recovery remains tentative. Our State of the Economy report also covers manufacturing, homebuilders, consumer sentiments, and more. To see the rest of the data, download our report for July 2020. We’ll be sharing a new report every month, so keep an eye out! Download Now

Do consumers pay certain types of credit accounts before others during financial distress? For instance, do they prioritize paying mortgage bills over credit card bills or personal loans? During the Great Recession, the traditional notion of payment priority among multiple credit accounts was upended, throwing strategies employed by financial institutions into disarray. Similarly, current circumstances in the context of COVID-19 might cause sudden shifts in prioritization of payments which might have a dramatic impact on your credit portfolio. Financial institutions would be better able to forecast and control exposure to credit risk, and to optimize servicing practices such as forbearance and collections treatments if they could understand changing customer payment behaviors and priorities of their existing customers across all open trades. Unfortunately, financial institutions’ data—including their own behavioral data and refreshed credit bureau data--are limited to information about their own portfolio. Experian data provides insight which complements the financial institutions’ data expanding understanding of consumer payment behavior and priorities spanning all trades. Experian recently completed a study aimed at providing financial institutions valuable insights about their customer portfolios prior to COVID-19 and during the initial months of COVID-19. Using the Experian Ascend Technology Platform™, our data scientists evaluated a random 10% sample of U.S. consumers from its national credit file. Data from multiple vintages were pulled (June 2006, June 2008 and February 2018) and the payment trends were studied over the subsequent performance period. Experian tabulated the counts of consumers who had various combinations of open and active trade types and selected several trade type combinations with volume to differentiate performance by trade type. The selected combinations collectively span a variety of scenarios involving six trade types (Auto Loans, Bankcard, Student Loan, Unsecured Personal Loans, Retail Cards and First Mortgages). The trade combinations selected accommodate a variety of lenders offering different products. For each of the consumer groups identified, Experian calculated default rates associated with each trade type across several performance periods. For brevity, this blog will focus on customers identified as of February 2018 and their subsequent performance through February 2020. As the recession evolves and when the economy eventually recovers, we will continue to monitor the impacts of COVID-19 on consumer payment behavior and priorities and share updates to this analysis. Consumers with Bankcard, Mortgage, Auto and Retail accounts Among consumers having open and recently active Bankcard, Mortgage, Auto and Retail accounts, bankcard delinquency was highest throughout the 24-month performance window, followed by Retail. Delinquency rates for Auto and Mortgage were the lowest. During the pre-COVID-19 period, consumers paid their secured loans before their unsecured loans. As demonstrated in the table below, customer payment priority was stable across the entire 24-month period, with no significant shift in payment priorities between trade types. Consumers with Unsecured Personal Loan, Retail Card and Bankcard accounts. Among consumers having open and recently active Unsecured Personal Loan, Retail Card and Bankcard accounts, consumers are likely to pay unsecured personal loans first when in financial distress. Retail is the second priority, followed by Bankcard. KEY FINDINGS From February 2018 through April 2020, relative payment priority by trade type has been stable Auto and Mortgage trades, when present, show very high payment priority Download the full Payment Hierarchy Report here. Download Now Learn more about how Experian can create a custom payment hierarchy for the customers in your own portfolio, contact your Experian Account Executive, or visit our website.

Consumer sentiment can help automotive marketers create a more human connection with consumers.

Experian recently released its Q1 2020 Market Trends report, which provides insights about the vehicles on the road and the most popular vehicle segments.

Origination data from April and May provide some insight into the more immediate effects of the pandemic on the automotive industry.

Experian’s Chris Ryan and Bobbie Paul recently re-joined David Mattei from Aite to discuss how emerging fraud trends and changes in consumer behavior will have long-term impacts on businesses. Chris, Bobbie, and David have combined experience of more than 60 years in the world of fraud prevention. In this discussion, they bring that experience to bear as they review how businesses should revise their long-term fraud strategy in response to COVID-19 and the subsequent economic shifts, including: The requirements to authenticate a digital customer Businesses’ technology challenges Differentiating between first party and third party fraud The importance of businesses’ technology investment How to build a roadmap for the next 90 days and beyond Experian · Make Your Fraud Plan Recession-Ready: Your 90 Day and Beyond Plan

Pre COVID-19, operations functions for retailers and financial institutions had not typically consisted of a remote (stay at home) workforce. Some organizations were better prepared than others, but there is a firm belief that retail and banking have changed for good as a result of the pandemic and resulting economic and workforce shifts. Market trends and implications When stay at home orders were issued, non-essential brick and mortar businesses closed unexpectedly. What were retailers to do with no traffic coming through the doors at their physical locations? The impact on big-box retailers like Best Buy, Dick’s Sporting goods, Sears, JCPenney, Nike, Starbucks, Macy’s, Neiman Marcus, Nordstrom, Kohl’s to name a few, has been unprecedented; some have had to shut their doors for good. Over the past several months global retail has seen e-commerce sales grow over 81% compared to the same period last year, according to Card Not Present. Some sectors have seen triple-digit growth year over year. Most online retailers have been ill-prepared to handle this increase in transactional volume in such a short amount of time, which has resulted in rapid fraud loss increases. A recent white paper from Aite Group reported that prior to COVID-19, a large financial institution forecasted an 8% decrease in fraud for 2020, but has since revised the projection to increase 10-15%. What does this all mean? Bad actors are taking advantage of the pandemic to exploit the online retail channel. The increased remote channel usage—online, mobile, and contact centers in particular—continues to be an area where retailers are exposed. Account takeover, through phishing and relaxed call center controls, is rising as well. Increases in phishing attacks are leading to compromised and stolen identities and synthetic identity fraud. Account takeover (ATO) fraud has increased 347% since 2019 according to PYMNTS.com. A recent survey found more than a quarter of merchants (27%) admit that they don’t have measures to prevent ATO. 24% of merchants can’t identify an ATO during a purchase. 14% of merchants say they are not even aware that an ATO has occurred unless a customer contacts them. When criminals use these compromised accounts to make fraudulent purchases, the merchant loses revenue and the value of the goods. They can also suffer from damage to brand reputation and a loss of customer confidence. A lack of account security can have lasting effects as 65% of customers surveyed say they would likely stop buying from a merchant if their account was compromised, according to that same Card Not Present study. So how can retailers start to identify bad actors with malicious intent? This will be a constant struggle for retailers. Rather than a one size fits all solution, retailers must move toward a strategy that is nimble and dynamic and can address multiple areas of exposure. A fraudster could easily slip by one verification method—for instance with a stolen credential—only to be foiled by a secondary authentication tactic like device identity. A layered fraud strategy continues to be the industry best practice, where both passive and active authentication methods are leveraged to frustrate fraudsters without applying undue friction to “good” consumers. The layered solution should also utilize device risk, identity verification and fraud analytics, with tailoring to each businesses’ needs, risk tolerance, and customer profiles. Learn more about how to build a layered fraud strategy today. Learn more

Experian’s own Chris Ryan and Bobbie Paul recently joined David Mattei from Aite to discuss the latest research and insights into emerging fraud schemes and how businesses can combat them in light of COVID-19 and the resulting economic changes. Between them, Chris, Bobbie, and David have more than 60 years of experience in the world of fraud prevention. Listen in as they discuss how businesses can shape their fraud prevention plan in the short term, including: The impacts of the health crisis and physical distancing The rise of e-commerce and consumer digital engagement Changes in criminal activity Fraud attack vectors 2020 fraud loss projections Critical next steps for the 30-60 day time frame Experian · Make Your Fraud Plan Recession-Ready: 2020 Fraud Trends

Account management is a critical strategy during any type of economy (pro-cycle, counter-cycle, cycle neutral). In times like these, marked by economic volatility, it is an effective way to identify which parts of your portfolio and which of your consumers need the most attention. Check out this podcast where Cyndy Chang, Senior Director of Product Management, and Craig Wilson, Senior Director of Consulting, discuss the foundational elements of account management, best practices and use cases. Account management today looks very different than what it has been during over a decade of growth proactive; account review is a critical part of navigating the path forward. Questions that need to be addressed include: Do you have the right data? Are you monitoring between data loads? Are you reviewing accounts at the frequency that today’s changing demands require? Listen in on the discussion to learn more. Experian · Look Ahead Podcast

In Q1 2020, 30-day delinquencies decreased from 1.98 percent in Q1 2019 to 1.93 percent, while 60-day delinquencies dropped from 0.68 percent to 0.67.